Meta-Analysis of Microarray Studies Reveals a Novel Hematopoietic Progenitor Cell Signature and Demonstrates Feasibility of Inter-Platform Data Integration
Open Access
- 13 August 2008
- journal article
- review article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 3 (8), e2965
- https://doi.org/10.1371/journal.pone.0002965
Abstract
Microarray-based studies of global gene expression (GE) have resulted in a large amount of data that can be mined for further insights into disease and physiology. Meta-analysis of these data is hampered by technical limitations due to many different platforms, gene annotations and probes used in different studies. We tested the feasibility of conducting a meta-analysis of GE studies to determine a transcriptional signature of hematopoietic progenitor and stem cells. Data from studies that used normal bone marrow-derived hematopoietic progenitors was integrated using both RefSeq and UniGene identifiers. We observed that in spite of variability introduced by experimental conditions and different microarray platforms, our meta-analytical approach can distinguish biologically distinct normal tissues by clustering them based on their cell of origin. When studied in terms of disease states, GE studies of leukemias and myelodysplasia progenitors tend to cluster with normal progenitors and remain distinct from other normal tissues, further validating the discriminatory power of this meta-analysis. Furthermore, analysis of 57 normal hematopoietic stem and progenitor cell GE samples was used to determine a gene expression signature characteristic of these cells. Genes that were most uniformly expressed in progenitors and at the same time differentially expressed when compared to other normal tissues were found to be involved in important biological processes such as cell cycle regulation and hematopoiesis. Validation studies using a different microarray platform demonstrated the enrichment of several genes such as SMARCE, Septin 6 and others not previously implicated in hematopoiesis. Most interestingly, alpha-integrin, the only common stemness gene discovered in a recent comparative murine analysis (Science 302(5644):393) was also enriched in our dataset, demonstrating the usefulness of this analytical approach.Keywords
This publication has 41 references indexed in Scilit:
- NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteinsNucleic Acids Research, 2007
- The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurementsNature Biotechnology, 2006
- A Bivalent Chromatin Structure Marks Key Developmental Genes in Embryonic Stem CellsCell, 2006
- Thousands of samples are needed to generate a robust gene list for predicting outcome in cancerProceedings of the National Academy of Sciences of the United States of America, 2006
- NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteinsNucleic Acids Research, 2004
- A gene atlas of the mouse and human protein-encoding transcriptomesProceedings of the National Academy of Sciences of the United States of America, 2004
- Evaluation of gene expression measurements from commercial microarray platformsNucleic Acids Research, 2003
- A Stem Cell Molecular SignatureScience, 2002
- "Stemness": Transcriptional Profiling of Embryonic and Adult Stem CellsScience, 2002
- Significance analysis of microarrays applied to the ionizing radiation responseProceedings of the National Academy of Sciences of the United States of America, 2001